All rights reservedSebastian Bergner, BenjaminSteffen, Daniel2024-03-072024-03-072015978-80-01-05782-7https://hdl.handle.net/20.500.14235/1400Book of proceedings: Annual AESOP Congress, Definite Space – Fuzzy Responsibility, Prague, 13-16th July, 2015With the rise of wearable technologies in the field of ambulatory assessment and commercial body monitoring products, the human being itself becomes a sensor of its immediate environment. In particular, user-generated vital data allows to draw conclusions from people’s emotions at every time and everywhere. This fact poses the question to what extent this data can be used for planning decision making. For decades, ambulatory assessment methods have been used to identify humans’ emotions linked to distinctive stimuli. The research is mostly done in laboratories under controlled conditions. Knowledge transfer to real world applications is still rare due to many uncontrollable environmental issues. Psychophysiological monitoring, however, shows high potential of transferability to real-world studies. If this user-generated emotion data is to be used for planning decision processes, many challenges have to be met: a) providing valid physiological, geo-referenced data in a real-world environment, b) preparing and processing data for following analyses, c) joining individual and environmental meta data, d) optimizing emerging visualizations and identifying emotional stimuli as basis for planning decision-making. The research at hand confronts these challenges, exemplified by a case study in the field of urban safety and security. It aims at identifying stress eliciting stimuli during an open air event. The methodical approach comprises physiological data collection and analyses, standardized questionnaires of stress experience and event perception, subjective self-assessments and spatial analyses of the surroundings as well as the combination of the results in different GIS-based visualization techniques.EnglishopenAccessEmotionsGIS-based VisualizationEvent MonitoringconferenceObject2216-2230